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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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200 staff and ~60 Ph.D. students. Please read more about the department’s work at https://www.uu.se/en/department/cell-and-molecular-biology . This position is based in Johan Elf’s research group
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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picture recognition. Strong background in machine learning, statistical modeling, and big-data analytics. Experience with infrastructure or transportation data or traffic planning (e.g. micro-simulation
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scenarios. The research combines field experiments, AI-based analysis of museum specimens, and advanced climate modeling to provide process-based insights into the ecological and economic consequences
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for functional reactor or fluidic systems. Experience with high-speed imaging, pressure measurements, or cavitation evaluation. Demonstrated ability to work independently while maintaining strong collaborative
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systems for diagnostics and treatment. Core activities include signal processing, antenna design, and measurement hardware development. Building complete prototype systems for clinical testing is a central
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring